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2020 – today
- 2024
[c102]Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith:
Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract. COLT 2024: 750-751- [c101]Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, Hugh Brendan McMahan, Vinith Menon Suriyakumar:
One-shot Empirical Privacy Estimation for Federated Learning. ICLR 2024 - [c100]Wei-Ning Chen, Berivan Isik, Peter Kairouz, Albert No, Sewoong Oh, Zheng Xu:
Improved Communication-Privacy Trade-offs in L2 Mean Estimation under Streaming Differential Privacy. ICML 2024 - [c99]S. Ashwin Hebbar, Sravan Kumar Ankireddy, Hyeji Kim, Sewoong Oh, Pramod Viswanath:
DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning. ICML 2024 - [c98]Da Yu, Peter Kairouz, Sewoong Oh, Zheng Xu:
Privacy-Preserving Instructions for Aligning Large Language Models. ICML 2024 - [c97]Liang Zhang, Bingcong Li, Kiran Koshy Thekumparampil, Sewoong Oh, Niao He:
DPZero: Private Fine-Tuning of Language Models without Backpropagation. ICML 2024 - [c96]Boxin Wang, Yibo Zhang, Yuan Cao, Bo Li, Hugh McMahan, Sewoong Oh, Zheng Xu, Manzil Zaheer:
Can Public Large Language Models Help Private Cross-device Federated Learning? NAACL-HLT (Findings) 2024: 934-949 - [i110]S. Ashwin Hebbar, Sravan Kumar Ankireddy, Hyeji Kim, Sewoong Oh, Pramod Viswanath:
DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning. CoRR abs/2402.08864 (2024) - [i109]Da Yu, Peter Kairouz, Sewoong Oh, Zheng Xu:
Privacy-Preserving Instructions for Aligning Large Language Models. CoRR abs/2402.13659 (2024) - [i108]Shuqi Ke, Charlie Hou, Giulia Fanti, Sewoong Oh:
On the Convergence of Differentially-Private Fine-tuning: To Linearly Probe or to Fully Fine-tune? CoRR abs/2402.18905 (2024) - [i107]Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith:
Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares. CoRR abs/2404.15409 (2024) - [i106]Wei-Ning Chen, Berivan Isik, Peter Kairouz, Albert No, Sewoong Oh, Zheng Xu:
Improved Communication-Privacy Trade-offs in L2 Mean Estimation under Streaming Differential Privacy. CoRR abs/2405.02341 (2024) - [i105]Eugene Bagdasaryan, Ren Yi, Sahra Ghalebikesabi, Peter Kairouz, Marco Gruteser, Sewoong Oh, Borja Balle, Daniel Ramage:
Air Gap: Protecting Privacy-Conscious Conversational Agents. CoRR abs/2405.05175 (2024) - [i104]Thao Nguyen, Matthew Wallingford, Sebastin Santy, Wei-Chiu Ma, Sewoong Oh, Ludwig Schmidt, Pang Wei Koh, Ranjay Krishna:
Multilingual Diversity Improves Vision-Language Representations. CoRR abs/2405.16915 (2024) - [i103]Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar:
DataComp-LM: In search of the next generation of training sets for language models. CoRR abs/2406.11794 (2024) - [i102]Anshul Nasery, Jonathan Hayase, Pang Wei Koh, Sewoong Oh:
PLeaS - Merging Models with Permutations and Least Squares. CoRR abs/2407.02447 (2024) - [i101]Divyansh Pareek, Simon S. Du, Sewoong Oh:
Understanding the Gains from Repeated Self-Distillation. CoRR abs/2407.04600 (2024) - [i100]Jonathan Hayase, Alisa Liu, Yejin Choi, Sewoong Oh, Noah A. Smith:
Data Mixture Inference: What do BPE Tokenizers Reveal about their Training Data? CoRR abs/2407.16607 (2024) - [i99]Thao Nguyen, Jeffrey Li, Sewoong Oh, Ludwig Schmidt, Jason Weston, Luke Zettlemoyer, Xian Li:
Better Alignment with Instruction Back-and-Forth Translation. CoRR abs/2408.04614 (2024) - [i98]Wei-Ning Chen, Peter Kairouz, Sewoong Oh, Zheng Xu:
Randomization Techniques to Mitigate the Risk of Copyright Infringement. CoRR abs/2408.13278 (2024) - [i97]Zerui Cheng, Edoardo Contente, Ben Finch, Oleg Golev, Jonathan Hayase, Andrew Miller, Niusha Moshrefi, Anshul Nasery, Sandeep Nailwal, Sewoong Oh, Himanshu Tyagi, Pramod Viswanath:
OML: Open, Monetizable, and Loyal AI. IACR Cryptol. ePrint Arch. 2024: 1573 (2024) - [i96]Marshall Ball, James Bell-Clark, Adrià Gascón, Peter Kairouz, Sewoong Oh, Zhiye Xie:
Secure Stateful Aggregation: A Practical Protocol with Applications in Differentially-Private Federated Learning. IACR Cryptol. ePrint Arch. 2024: 1655 (2024) - 2023
- [j30]Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
MAUVE Scores for Generative Models: Theory and Practice. J. Mach. Learn. Res. 24: 356:1-356:92 (2023) - [j29]Mohammad Vahid Jamali
, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
Machine Learning-Aided Efficient Decoding of Reed-Muller Subcodes. IEEE J. Sel. Areas Inf. Theory 4: 260-275 (2023) - [j28]Shuaiqi Wang, Jonathan Hayase, Giulia Fanti, Sewoong Oh:
Towards a Defense Against Federated Backdoor Attacks Under Continuous Training. Trans. Mach. Learn. Res. 2023 (2023) - [c95]Zheng Xu, Maxwell D. Collins, Yuxiao Wang, Liviu Panait, Sewoong Oh, Sean Augenstein, Ting Liu, Florian Schroff, H. Brendan McMahan:
Learning to Generate Image Embeddings with User-Level Differential Privacy. CVPR 2023: 7969-7980 - [c94]Jonathan Hayase, Sewoong Oh:
Few-shot Backdoor Attacks via Neural Tangent Kernels. ICLR 2023 - [c93]Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Guha Thakurta, Lun Wang:
Why Is Public Pretraining Necessary for Private Model Training? ICML 2023: 10611-10627 - [c92]S. Ashwin Hebbar, Viraj Vivek Nadkarni, Ashok Vardhan Makkuva, Suma Bhat, Sewoong Oh, Pramod Viswanath:
CRISP: Curriculum based Sequential neural decoders for Polar code family. ICML 2023: 12823-12845 - [c91]Enayat Ullah, Christopher A. Choquette-Choo, Peter Kairouz, Sewoong Oh:
Private Federated Learning with Autotuned Compression. ICML 2023: 34668-34708 - [c90]Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander J. Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. NeurIPS 2023 - [c89]Rishi D. Jha, Jonathan Hayase, Sewoong Oh:
Label Poisoning is All You Need. NeurIPS 2023 - [c88]Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala:
Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency. NeurIPS 2023 - [c87]Daogao Liu, Arun Ganesh, Sewoong Oh, Abhradeep Guha Thakurta:
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks. NeurIPS 2023 - [c86]Thao Nguyen, Samir Yitzhak Gadre, Gabriel Ilharco, Sewoong Oh, Ludwig Schmidt:
Improving multimodal datasets with image captioning. NeurIPS 2023 - [c85]Krishna Pillutla, Galen Andrew, Peter Kairouz, H. Brendan McMahan, Alina Oprea, Sewoong Oh:
Unleashing the Power of Randomization in Auditing Differentially Private ML. NeurIPS 2023 - [c84]Vivek Ramanujan, Thao Nguyen, Sewoong Oh, Ali Farhadi, Ludwig Schmidt:
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness. NeurIPS 2023 - [i95]Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
Machine Learning-Aided Efficient Decoding of Reed-Muller Subcodes. CoRR abs/2301.06251 (2023) - [i94]Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala:
Near Optimal Private and Robust Linear Regression. CoRR abs/2301.13273 (2023) - [i93]Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, H. Brendan McMahan, Vinith M. Suriyakumar:
One-shot Empirical Privacy Estimation for Federated Learning. CoRR abs/2302.03098 (2023) - [i92]Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Thakurta, Lun Wang:
Why Is Public Pretraining Necessary for Private Model Training? CoRR abs/2302.09483 (2023) - [i91]Arun Ganesh, Daogao Liu, Sewoong Oh, Abhradeep Thakurta:
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks. CoRR abs/2302.09699 (2023) - [i90]Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Matthew Jagielski, Yangsibo Huang, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie J. Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Sergey Yekhanin, Da Yu, Huanyu Zhang, Wanrong Zhang:
Challenges towards the Next Frontier in Privacy. CoRR abs/2304.06929 (2023) - [i89]Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. CoRR abs/2304.14108 (2023) - [i88]Boxin Wang, Jacky Yibo Zhang, Yuan Cao, Bo Li, H. Brendan McMahan, Sewoong Oh, Zheng Xu, Manzil Zaheer:
Can Public Large Language Models Help Private Cross-device Federated Learning? CoRR abs/2305.12132 (2023) - [i87]Krishna Pillutla, Galen Andrew, Peter Kairouz, H. Brendan McMahan, Alina Oprea, Sewoong Oh:
Unleashing the Power of Randomization in Auditing Differentially Private ML. CoRR abs/2305.18447 (2023) - [i86]Thao Nguyen, Samir Yitzhak Gadre, Gabriel Ilharco, Sewoong Oh, Ludwig Schmidt:
Improving Multimodal Datasets with Image Captioning. CoRR abs/2307.10350 (2023) - [i85]Enayat Ullah, Christopher A. Choquette-Choo, Peter Kairouz, Sewoong Oh:
Private Federated Learning with Autotuned Compression. CoRR abs/2307.10999 (2023) - [i84]Vivek Ramanujan, Thao Nguyen, Sewoong Oh, Ludwig Schmidt, Ali Farhadi:
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness. CoRR abs/2307.12532 (2023) - [i83]Liam Collins, Shanshan Wu, Sewoong Oh, Khe Chai Sim:
Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning. CoRR abs/2310.04627 (2023) - [i82]Liang Zhang, Kiran Koshy Thekumparampil, Sewoong Oh, Niao He:
DPZero: Dimension-Independent and Differentially Private Zeroth-Order Optimization. CoRR abs/2310.09639 (2023) - [i81]Rishi D. Jha, Jonathan Hayase, Sewoong Oh:
Label Poisoning is All You Need. CoRR abs/2310.18933 (2023) - 2022
- [c83]Kiran Koshy Thekumparampil, Niao He, Sewoong Oh:
Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization. AISTATS 2022: 4281-4308 - [c82]Sen Lin, Ming Shi, Anish Arora, Raef Bassily, Elisa Bertino, Constantine Caramanis, Kaushik R. Chowdhury, Eylem Ekici, Atilla Eryilmaz, Stratis Ioannidis, Nan Jiang, Gauri Joshi, Jim Kurose, Yingbin Liang, Zhiqiang Lin, Jia Liu, Mingyan Liu, Tommaso Melodia, Aryan Mokhtari, Rob Nowak, Sewoong Oh, Srini Parthasarathy, Chunyi Peng, Hulya Seferoglu, Ness B. Shroff, Sanjay Shakkottai, Kannan Srinivasan, Ameet Talwalkar, Aylin Yener, Lei Ying:
Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks. CIC 2022: 16-25 - [c81]Xiyang Liu, Weihao Kong, Sewoong Oh:
Differential privacy and robust statistics in high dimensions. COLT 2022: 1167-1246 - [c80]Vivek Kumar Bagaria, Amir Dembo, Sreeram Kannan, Sewoong Oh, David Tse, Pramod Viswanath, Xuechao Wang, Ofer Zeitouni:
Proof-of-Stake Longest Chain Protocols: Security vs Predictability. ConsensusDay@CCS 2022: 29-42 - [c79]Charlie Hou, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh:
FedChain: Chained Algorithms for Near-optimal Communication Cost in Federated Learning. ICLR 2022 - [c78]Xingyu Wang, Sewoong Oh, Chang-Han Rhee:
Eliminating Sharp Minima from SGD with Truncated Heavy-tailed Noise. ICLR 2022 - [c77]Liam Collins, Aryan Mokhtari, Sewoong Oh, Sanjay Shakkottai:
MAML and ANIL Provably Learn Representations. ICML 2022: 4238-4310 - [c76]Melih Yilmaz, William Fondrie, Wout Bittremieux, Sewoong Oh, William S. Noble:
De novo mass spectrometry peptide sequencing with a transformer model. ICML 2022: 25514-25522 - [c75]Matt Jordan, Jonathan Hayase, Alex Dimakis, Sewoong Oh:
Zonotope Domains for Lagrangian Neural Network Verification. NeurIPS 2022 - [c74]Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh:
DP-PCA: Statistically Optimal and Differentially Private PCA. NeurIPS 2022 - [c73]Thao Nguyen, Gabriel Ilharco, Mitchell Wortsman, Sewoong Oh, Ludwig Schmidt:
Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP. NeurIPS 2022 - [c72]Liang Zhang, Kiran Koshy Thekumparampil, Sewoong Oh, Niao He:
Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization. NeurIPS 2022 - [i80]Kiran Koshy Thekumparampil, Niao He, Sewoong Oh:
Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization. CoRR abs/2201.07427 (2022) - [i79]Liam Collins, Aryan Mokhtari, Sewoong Oh, Sanjay Shakkottai:
MAML and ANIL Provably Learn Representations. CoRR abs/2202.03483 (2022) - [i78]Shuaiqi Wang, Jonathan Hayase, Giulia Fanti, Sewoong Oh:
Towards a Defense against Backdoor Attacks in Continual Federated Learning. CoRR abs/2205.11736 (2022) - [i77]Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh:
DP-PCA: Statistically Optimal and Differentially Private PCA. CoRR abs/2205.13709 (2022) - [i76]Liang Zhang, Kiran Koshy Thekumparampil, Sewoong Oh, Niao He:
Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization. CoRR abs/2206.00363 (2022) - [i75]Thao Nguyen, Gabriel Ilharco, Mitchell Wortsman, Sewoong Oh, Ludwig Schmidt:
Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP. CoRR abs/2208.05516 (2022) - [i74]S. Ashwin Hebbar, Viraj Nadkarni, Ashok Vardhan Makkuva, Suma Bhat, Sewoong Oh, Pramod Viswanath:
CRISP: Curriculum based Sequential Neural Decoders for Polar Code Family. CoRR abs/2210.00313 (2022) - [i73]Zaïd Harchaoui, Sewoong Oh, Soumik Pal, Raghav Somani, Raghavendra Tripathi:
Stochastic optimization on matrices and a graphon McKean-Vlasov limit. CoRR abs/2210.00422 (2022) - [i72]Jonathan Hayase, Sewoong Oh:
Few-shot Backdoor Attacks via Neural Tangent Kernels. CoRR abs/2210.05929 (2022) - [i71]Matt Jordan, Jonathan Hayase, Alexandros G. Dimakis, Sewoong Oh:
Zonotope Domains for Lagrangian Neural Network Verification. CoRR abs/2210.08069 (2022) - [i70]Zheng Xu, Maxwell D. Collins, Yuxiao Wang, Liviu Panait, Sewoong Oh, Sean Augenstein, Ting Liu, Florian Schroff, H. Brendan McMahan:
Learning to Generate Image Embeddings with User-level Differential Privacy. CoRR abs/2211.10844 (2022) - [i69]Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
MAUVE Scores for Generative Models: Theory and Practice. CoRR abs/2212.14578 (2022) - 2021
- [c71]Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh:
Defense against backdoor attacks via robust covariance estimation. ICML 2021: 4129-4139 - [c70]Ashok Vardhan Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning. ICML 2021: 7368-7378 - [c69]Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
Reed-Muller Subcodes: Machine Learning-Aided Design of Efficient Soft Recursive Decoding. ISIT 2021: 1088-1093 - [c68]Xiyang Liu, Weihao Kong, Sham M. Kakade, Sewoong Oh:
Robust and differentially private mean estimation. NeurIPS 2021: 3887-3901 - [c67]Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals. NeurIPS 2021: 12930-12942 - [c66]Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh:
Statistically and Computationally Efficient Linear Meta-representation Learning. NeurIPS 2021: 18487-18500 - [c65]Jinwoo Jeon, Jaechang Kim, Kangwook Lee, Sewoong Oh, Jungseul Ok:
Gradient Inversion with Generative Image Prior. NeurIPS 2021: 29898-29908 - [i68]Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
Reed-Muller Subcodes: Machine Learning-Aided Design of Efficient Soft Recursive Decoding. CoRR abs/2102.01671 (2021) - [i67]Xingyu Wang, Sewoong Oh, Chang-Han Rhee:
Eliminating Sharp Minima from SGD with Truncated Heavy-tailed Noise. CoRR abs/2102.04297 (2021) - [i66]Charlie Hou, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh:
Efficient Algorithms for Federated Saddle Point Optimization. CoRR abs/2102.06333 (2021) - [i65]Xiyang Liu, Weihao Kong, Sham M. Kakade, Sewoong Oh:
Robust and Differentially Private Mean Estimation. CoRR abs/2102.09159 (2021) - [i64]Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh:
SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics. CoRR abs/2104.11315 (2021) - [i63]Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh:
Sample Efficient Linear Meta-Learning by Alternating Minimization. CoRR abs/2105.08306 (2021) - [i62]Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral. CoRR abs/2106.07898 (2021) - [i61]Charlie Hou, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh:
Reducing the Communication Cost of Federated Learning through Multistage Optimization. CoRR abs/2108.06869 (2021) - [i60]Ashok Vardhan Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
KO codes: Inventing Nonlinear Encoding and Decoding for Reliable Wireless Communication via Deep-learning. CoRR abs/2108.12920 (2021) - [i59]Jinwoo Jeon, Jaechang Kim, Kangwook Lee, Sewoong Oh, Jungseul Ok:
Gradient Inversion with Generative Image Prior. CoRR abs/2110.14962 (2021) - [i58]Xiyang Liu, Weihao Kong, Sewoong Oh:
Differential privacy and robust statistics in high dimensions. CoRR abs/2111.06578 (2021) - [i57]Sewoong Oh, Soumik Pal, Raghav Somani, Raghav Tripathi:
Gradient flows on graphons: existence, convergence, continuity equations. CoRR abs/2111.09459 (2021) - 2020
- [j27]Richard G. Baraniuk, Alex Dimakis, Negar Kiyavash, Sewoong Oh, Rebecca Willett:
Guest Editorial. IEEE J. Sel. Areas Inf. Theory 1(1): 4 (2020) - [j26]Hyeji Kim, Sewoong Oh, Pramod Viswanath:
Physical Layer Communication via Deep Learning. IEEE J. Sel. Areas Inf. Theory 1(1): 5-18 (2020) - [j25]Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Deepcode: Feedback Codes via Deep Learning. IEEE J. Sel. Areas Inf. Theory 1(1): 194-206 (2020) - [j24]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
LEARN Codes: Inventing Low-Latency Codes via Recurrent Neural Networks. IEEE J. Sel. Areas Inf. Theory 1(1): 207-216 (2020) - [j23]Zinan Lin, Ashish Khetan, Giulia Fanti, Sewoong Oh:
PacGAN: The Power of Two Samples in Generative Adversarial Networks. IEEE J. Sel. Areas Inf. Theory 1(1): 324-335 (2020) - [j22]Weizhao Tang, Weina Wang, Giulia Fanti, Sewoong Oh:
Privacy-Utility Tradeoffs in Routing Cryptocurrency over Payment Channel Networks. Proc. ACM Meas. Anal. Comput. Syst. 4(2): 29:1-29:39 (2020) - [c64]Ashok Vardhan Makkuva, Sewoong Oh, Sreeram Kannan, Pramod Viswanath:
Learning in Gated Neural Networks. AISTATS 2020: 3338-3348 - [c63]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sewoong Oh, Sreeram Kannan, Pramod Viswanath:
Feedback Turbo Autoencoder. ICASSP 2020: 8559-8563 - [c62]Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh:
Meta-learning for Mixed Linear Regression. ICML 2020: 5394-5404 - [c61]Zinan Lin, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh:
InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs. ICML 2020: 6127-6139 - [c60]Ashok Vardhan Makkuva, Amirhossein Taghvaei, Sewoong Oh, Jason D. Lee:
Optimal transport mapping via input convex neural networks. ICML 2020: 6672-6681 - [c59]Weihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh:
Robust Meta-learning for Mixed Linear Regression with Small Batches. NeurIPS 2020 - [c58]Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh:
Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method. NeurIPS 2020 - [c57]Weizhao Tang, Weina Wang, Giulia Fanti, Sewoong Oh:
Privacy-Utility Tradeoffs in Routing Cryptocurrency over Payment Channel Networks. SIGMETRICS (Abstracts) 2020: 81-82 - [c56]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Joint Channel Coding and Modulation via Deep Learning. SPAWC 2020: 1-5 - [i56]Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh:
Meta-learning for mixed linear regression. CoRR abs/2002.08936 (2020) - [i55]Weihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh:
Robust Meta-learning for Mixed Linear Regression with Small Batches. CoRR abs/2006.09702 (2020) - [i54]Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Deepcode and Modulo-SK are Designed for Different Settings. CoRR abs/2008.07997 (2020) - [i53]Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh:
Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method. CoRR abs/2010.01848 (2020)
2010 – 2019
- 2019
- [j21]Ashish Khetan, Sewoong Oh:
Spectrum Estimation from a Few Entries. J. Mach. Learn. Res. 20: 21:1-21:55 (2019) - [c55]Jungseul Ok, Sewoong Oh, Yunhun Jang, Jinwoo Shin, Yung Yi:
Iterative Bayesian Learning for Crowdsourced Regression. AISTATS 2019: 1486-1495 - [c54]Weihao Gao, Ashok Vardhan Makkuva, Sewoong Oh, Pramod Viswanath:
Learning One-hidden-layer Neural Networks under General Input Distributions. AISTATS 2019: 1950-1959 - [c53]Giulia Fanti, Leonid Kogan, Sewoong Oh, Kathleen Ruan, Pramod Viswanath, Gerui Wang:
Compounding of Wealth in Proof-of-Stake Cryptocurrencies. Financial Cryptography 2019: 42-61 - [c52]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
LEARN Codes: Inventing Low-Latency Codes via Recurrent Neural Networks. ICC 2019: 1-7 - [c51]Weihao Gao, Yu-Han Liu, Chong Wang, Sewoong Oh:
Rate Distortion For Model Compression: From Theory To Practice. ICML 2019: 2102-2111 - [c50]Ashok Vardhan Makkuva, Pramod Viswanath, Sreeram Kannan, Sewoong Oh:
Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms. ICML 2019: 4304-4313 - [c49]Giulia Fanti, Jiantao Jiao, Ashok Vardhan Makkuva, Sewoong Oh, Ranvir Rana, Pramod Viswanath:
Barracuda: The Power of ℓ-polling in Proof-of-Stake Blockchains. MobiHoc 2019: 351-360 - [c48]Xiyang Liu, Sewoong Oh:
Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases. NeurIPS 2019: 2414-2425 - [c47]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels. NeurIPS 2019: 2754-2764 - [c46]Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh:
Efficient Algorithms for Smooth Minimax Optimization. NeurIPS 2019: 12659-12670 - [c45]Yihan Jiang, Sreeram Kannan, Hyeji Kim, Sewoong Oh, Himanshu Asnani, Pramod Viswanath:
DEEPTURBO: Deep Turbo Decoder. SPAWC 2019: 1-5 - [i52]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
DeepTurbo: Deep Turbo Decoder. CoRR abs/1903.02295 (2019) - [i51]Xiyang Liu, Sewoong Oh:
Minimax Rates of Estimating Approximate Differential Privacy. CoRR abs/1905.10335 (2019) - [i50]Ashok Vardhan Makkuva, Sewoong Oh, Sreeram Kannan, Pramod Viswanath:
Learning in Gated Neural Networks. CoRR abs/1906.02777 (2019) - [i49]Kiran Koshy Thekumparampil, Sewoong Oh, Ashish Khetan:
Robust conditional GANs under missing or uncertain labels. CoRR abs/1906.03579 (2019) - [i48]Zinan Lin, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh:
InfoGAN-CR: Disentangling Generative Adversarial Networks with Contrastive Regularizers. CoRR abs/1906.06034 (2019) - [i47]Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh:
Efficient Algorithms for Smooth Minimax Optimization. CoRR abs/1907.01543 (2019) - [i46]Ashok Vardhan Makkuva, Amirhossein Taghvaei, Sewoong Oh, Jason D. Lee:
Optimal transport mapping via input convex neural networks. CoRR abs/1908.10962 (2019) - [i45]Weizhao Tang, Weina Wang, Giulia Fanti, Sewoong Oh:
Privacy-Utility Tradeoffs in Routing Cryptocurrency over Payment Channel Networks. CoRR abs/1909.02717 (2019) - [i44]Giulia Fanti, Jiantao Jiao, Ashok Vardhan Makkuva, Sewoong Oh, Ranvir Rana, Pramod Viswanath:
Barracuda: The Power of 𝓁-polling in Proof-of-Stake Blockchains. CoRR abs/1909.08719 (2019) - [i43]Xuechao Wang, Govinda M. Kamath, Vivek Kumar Bagaria, Sreeram Kannan, Sewoong Oh, David Tse, Pramod Viswanath:
Proof-of-Stake Longest Chain Protocols Revisited. CoRR abs/1910.02218 (2019) - [i42]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels. CoRR abs/1911.03038 (2019) - 2018
- [j20]Ashish Khetan, Sewoong Oh:
Generalized Rank-Breaking: Computational and Statistical Tradeoffs. J. Mach. Learn. Res. 19: 28:1-28:42 (2018) - [j19]Sahand Negahban, Sewoong Oh, Kiran Koshy Thekumparampil, Jiaming Xu:
Learning from Comparisons and Choices. J. Mach. Learn. Res. 19: 40:1-40:95 (2018) - [j18]Weihao Gao, Sewoong Oh, Pramod Viswanath:
Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation. IEEE Trans. Inf. Theory 64(5): 3313-3330 (2018) - [j17]Weihao Gao, Sewoong Oh, Pramod Viswanath:
Demystifying Fixed k-Nearest Neighbor Information Estimators. IEEE Trans. Inf. Theory 64(8): 5629-5661 (2018) - [j16]Jungseul Ok, Sewoong Oh, Jinwoo Shin, Yung Yi:
Optimal Inference in Crowdsourced Classification via Belief Propagation. IEEE Trans. Inf. Theory 64(9): 6127-6138 (2018) - [c44]Hyeji Kim, Yihan Jiang, Ranvir Rana, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Communication Algorithms via Deep Learning. ICLR (Poster) 2018 - [c43]Zinan Lin, Ashish Khetan, Giulia Fanti, Sewoong Oh:
PacGAN: The power of two samples in generative adversarial networks. NeurIPS 2018: 1505-1514 - [c42]Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Deepcode: Feedback Codes via Deep Learning. NeurIPS 2018: 9458-9468 - [c41]Kiran Koshy Thekumparampil, Ashish Khetan, Zinan Lin, Sewoong Oh:
Robustness of conditional GANs to noisy labels. NeurIPS 2018: 10292-10303 - [i41]Kiran Koshy Thekumparampil, Chong Wang, Sewoong Oh, Li-Jia Li:
Attention-based Graph Neural Network for Semi-supervised Learning. CoRR abs/1803.03735 (2018) - [i40]Hyeji Kim, Yihan Jiang, Ranvir Rana, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Communication Algorithms via Deep Learning. CoRR abs/1805.09317 (2018) - [i39]Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Deepcode: Feedback Codes via Deep Learning. CoRR abs/1807.00801 (2018) - [i38]Giulia Fanti, Leonid Kogan, Sewoong Oh, Kathleen Ruan, Pramod Viswanath, Gerui Wang:
Compounding of Wealth in Proof-of-Stake Cryptocurrencies. CoRR abs/1809.07468 (2018) - [i37]Weihao Gao, Ashok Vardhan Makkuva, Sewoong Oh, Pramod Viswanath:
Learning One-hidden-layer Neural Networks under General Input Distributions. CoRR abs/1810.04133 (2018) - [i36]Weihao Gao, Chong Wang, Sewoong Oh:
Rate Distortion For Model Compression: From Theory To Practice. CoRR abs/1810.06401 (2018) - [i35]Kiran Koshy Thekumparampil, Ashish Khetan, Zinan Lin, Sewoong Oh:
Robustness of Conditional GANs to Noisy Labels. CoRR abs/1811.03205 (2018) - [i34]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
LEARN Codes: Inventing Low-latency Codes via Recurrent Neural Networks. CoRR abs/1811.12707 (2018) - [i33]Ashish Khetan, Harshay Shah, Sewoong Oh:
Number of Connected Components in a Graph: Estimation via Counting Patterns. CoRR abs/1812.00139 (2018) - 2017
- [j15]Hyeji Kim, Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Discovering Potential Correlations via Hypercontractivity. Entropy 19(11): 586 (2017) - [j14]Sahand Negahban, Sewoong Oh, Devavrat Shah:
Rank Centrality: Ranking from Pairwise Comparisons. Oper. Res. 65(1): 266-287 (2017) - [j13]Peter Kairouz, Sewoong Oh, Pramod Viswanath:
The Composition Theorem for Differential Privacy. IEEE Trans. Inf. Theory 63(6): 4037-4049 (2017) - [j12]Giulia Fanti, Peter Kairouz, Sewoong Oh, Kannan Ramchandran, Pramod Viswanath:
Hiding the Rumor Source. IEEE Trans. Inf. Theory 63(10): 6679-6713 (2017) - [c40]Weihao Gao, Sewoong Oh, Pramod Viswanath:
Demystifying fixed k-nearest neighbor information estimators. ISIT 2017: 1267-1271 - [c39]Weihao Gao, Sewoong Oh, Pramod Viswanath:
Density functional estimators with k-nearest neighbor bandwidths. ISIT 2017: 1351-1355 - [c38]Minje Jang, Sunghyun Kim, Changho Suh, Sewoong Oh:
Optimal Sample Complexity of M-wise Data for Top-K Ranking. NIPS 2017: 1686-1696 - [c37]Hyeji Kim, Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Discovering Potential Correlations via Hypercontractivity. NIPS 2017: 4577-4587 - [c36]Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Estimating Mutual Information for Discrete-Continuous Mixtures. NIPS 2017: 5986-5997 - [c35]Ashish Khetan, Sewoong Oh:
Matrix Norm Estimation from a Few Entries. NIPS 2017: 6424-6433 - [c34]Sewoong Oh:
Matrix Factorization at the Frontier of Non-convex Optimizations: Abstract for SIGMETRICS 2017 Rising Star Award Talk. SIGMETRICS (Abstracts) 2017: 62 - [e1]Bruce E. Hajek, Sewoong Oh, Augustin Chaintreau, Leana Golubchik, Zhi-Li Zhang:
Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Urbana-Champaign, IL, USA, June 05 - 09, 2017. ACM 2017, ISBN 978-1-4503-5032-7 [contents] - [i32]Weihao Gao, Sewoong Oh, Pramod Viswanath:
Density Functional Estimators with k-Nearest Neighbor Bandwidths. CoRR abs/1702.03051 (2017) - [i31]Jungseul Ok, Sewoong Oh, Jinwoo Shin, Yunhun Jang, Yung Yi:
Efficient Learning for Crowdsourced Regression. CoRR abs/1702.08840 (2017) - [i30]Ashish Khetan, Sewoong Oh:
Spectrum Estimation from a Few Entries. CoRR abs/1703.06327 (2017) - [i29]Sahand Negahban, Sewoong Oh, Kiran Koshy Thekumparampil, Jiaming Xu:
Learning from Comparisons and Choices. CoRR abs/1704.07228 (2017) - [i28]Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Estimating Mutual Information for Discrete-Continuous Mixtures. CoRR abs/1709.06212 (2017) - [i27]Zinan Lin, Ashish Khetan, Giulia Fanti, Sewoong Oh:
PacGAN: The power of two samples in generative adversarial networks. CoRR abs/1712.04086 (2017) - 2016
- [j11]Peter Kairouz, Sewoong Oh, Pramod Viswanath:
Extremal Mechanisms for Local Differential Privacy. J. Mach. Learn. Res. 17: 17:1-17:51 (2016) - [j10]Ashish Khetan, Sewoong Oh:
Data-driven Rank Breaking for Efficient Rank Aggregation. J. Mach. Learn. Res. 17: 193:1-193:54 (2016) - [j9]Subhashini Krishnasamy, Rajat Sen, Sanjay Shakkottai, Sewoong Oh:
Detecting Sponsored Recommendations. ACM Trans. Model. Perform. Evaluation Comput. Syst. 2(1): 6:1-6:29 (2016) - [j8]Giulia Fanti, Peter Kairouz, Sewoong Oh, Kannan Ramchandran, Pramod Viswanath:
Metadata-Conscious Anonymous Messaging. IEEE Trans. Signal Inf. Process. over Networks 2(4): 582-594 (2016) - [c33]Peter Kairouz, Sewoong Oh, Pramod Viswanath:
Differentially private multi-party computation. CISS 2016: 128-132 - [c32]Ashish Khetan, Sewoong Oh:
Data-driven Rank Breaking for Efficient Rank Aggregation. ICML 2016: 89-98 - [c31]Giulia Fanti, Peter Kairouz, Sewoong Oh, Kannan Ramchandran, Pramod Viswanath:
Metadata-conscious anonymous messaging. ICML 2016: 108-116 - [c30]Jungseul Ok, Sewoong Oh, Jinwoo Shin, Yung Yi:
Optimality of Belief Propagation for Crowdsourced Classification. ICML 2016: 535-544 - [c29]Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Conditional Dependence via Shannon Capacity: Axioms, Estimators and Applications. ICML 2016: 2780-2789 - [c28]Ashish Khetan, Sewoong Oh:
Computational and Statistical Tradeoffs in Learning to Rank. NIPS 2016: 739-747 - [c27]Weihao Gao, Sewoong Oh, Pramod Viswanath:
Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation. NIPS 2016: 2460-2468 - [c26]Ashish Khetan, Sewoong Oh:
Achieving budget-optimality with adaptive schemes in crowdsourcing. NIPS 2016: 4844-4852 - [c25]Giulia Fanti, Peter Kairouz, Sewoong Oh, Kannan Ramchandran, Pramod Viswanath:
Rumor Source Obfuscation on Irregular Trees. SIGMETRICS 2016: 153-164 - [i26]Ashish Khetan, Sewoong Oh:
Data-driven Rank Breaking for Efficient Rank Aggregation. CoRR abs/1601.05495 (2016) - [i25]Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Causal Strength via Shannon Capacity: Axioms, Estimators and Applications. CoRR abs/1602.03476 (2016) - [i24]Ashish Khetan, Sewoong Oh:
Reliable Crowdsourcing under the Generalized Dawid-Skene Model. CoRR abs/1602.03481 (2016) - [i23]Jungseul Ok, Sewoong Oh, Jinwoo Shin, Yung Yi:
Optimality of Belief Propagation for Crowdsourced Classification. CoRR abs/1602.03619 (2016) - [i22]Minje Jang, Sunghyun Kim, Changho Suh, Sewoong Oh:
Top-K Ranking from Pairwise Comparisons: When Spectral Ranking is Optimal. CoRR abs/1603.04153 (2016) - [i21]Weihao Gao, Sewoong Oh, Pramod Viswanath:
Demystifying Fixed k-Nearest Neighbor Information Estimators. CoRR abs/1604.03006 (2016) - [i20]Ashish Khetan, Sewoong Oh:
Computational and Statistical Tradeoffs in Learning to Rank. CoRR abs/1608.06203 (2016) - [i19]Weihao Gao, Sewoong Oh, Pramod Viswanath:
Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation. CoRR abs/1609.02208 (2016) - 2015
- [j7]Quan Geng, Peter Kairouz, Sewoong Oh, Pramod Viswanath:
The Staircase Mechanism in Differential Privacy. IEEE J. Sel. Top. Signal Process. 9(7): 1176-1184 (2015) - [c24]Peter Kairouz, Sewoong Oh, Pramod Viswanath:
The Composition Theorem for Differential Privacy. ICML 2015: 1376-1385 - [c23]Sewoong Oh, Kiran Koshy Thekumparampil, Jiaming Xu:
Collaboratively Learning Preferences from Ordinal Data. NIPS 2015: 1909-1917 - [c22]Peter Kairouz, Sewoong Oh, Pramod Viswanath:
Secure Multi-party Differential Privacy. NIPS 2015: 2008-2016 - [c21]Giulia Fanti, Peter Kairouz, Sewoong Oh, Pramod Viswanath:
Spy vs. Spy: Rumor Source Obfuscation. SIGMETRICS 2015: 271-284 - [c20]Subhashini Krishnasamy, Rajat Sen, Sewoong Oh, Sanjay Shakkottai:
Detecting Sponsored Recommendations. SIGMETRICS 2015: 445-446 - [i18]Subhashini Krishnasamy, Rajat Sen, Sewoong Oh, Sanjay Shakkottai:
Detecting Sponsored Recommendations. CoRR abs/1504.03713 (2015) - [i17]Sewoong Oh, Kiran Koshy Thekumparampil, Jiaming Xu:
Collaboratively Learning Preferences from Ordinal Data. CoRR abs/1506.07947 (2015) - [i16]Giulia Fanti, Peter Kairouz, Sewoong Oh, Kannan Ramchandran, Pramod Viswanath:
Hiding the Rumor Source. CoRR abs/1509.02849 (2015) - 2014
- [j6]David R. Karger, Sewoong Oh, Devavrat Shah:
Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems. Oper. Res. 62(1): 1-24 (2014) - [c19]Prateek Jain, Sewoong Oh:
Learning Mixtures of Discrete Product Distributions using Spectral Decompositions. COLT 2014: 824-856 - [c18]Sewoong Oh, Devavrat Shah:
Learning Mixed Multinomial Logit Model from Ordinal Data. NIPS 2014: 595-603 - [c17]Prateek Jain, Sewoong Oh:
Provable Tensor Factorization with Missing Data. NIPS 2014: 1431-1439 - [c16]Bruce E. Hajek, Sewoong Oh, Jiaming Xu:
Minimax-optimal Inference from Partial Rankings. NIPS 2014: 1475-1483 - [c15]Peter Kairouz, Sewoong Oh, Pramod Viswanath:
Extremal Mechanisms for Local Differential Privacy. NIPS 2014: 2879-2887 - [c14]Dongwoo Kang, Wooseong Shim, Sewoong Oh, Sunyoung Kim:
Assessment of ENC sounding by Delaunay Triangulation method in aspect of fine compilation for safe navigation. SCIS&ISIS 2014: 226-230 - [c13]Ammar Ammar, Sewoong Oh, Devavrat Shah, Luis Filipe Voloch:
What's your choice?: learning the mixed multi-nomial. SIGMETRICS 2014: 565-566 - [i15]Peter Kairouz, Sewoong Oh, Pramod Viswanath:
Extremal Mechanisms for Local Differential Privacy. CoRR abs/1407.1338 (2014) - [i14]Peter Kairouz, Sewoong Oh, Pramod Viswanath:
Optimality of Non-Interactive Randomized Response. CoRR abs/1407.1546 (2014) - [i13]Peter Kairouz, Sewoong Oh, Pramod Viswanath:
Spy vs. Spy: Rumor Source Obfuscation. CoRR abs/1412.8439 (2014) - 2013
- [j5]Amin Karbasi, Sewoong Oh:
Robust Localization From Incomplete Local Information. IEEE/ACM Trans. Netw. 21(4): 1131-1144 (2013) - [j4]Reza Parhizkar, Amin Karbasi, Sewoong Oh, Martin Vetterli:
Calibration Using Matrix Completion With Application to Ultrasound Tomography. IEEE Trans. Signal Process. 61(20): 4923-4933 (2013) - [c12]David R. Karger, Sewoong Oh, Devavrat Shah:
Efficient crowdsourcing for multi-class labeling. SIGMETRICS 2013: 81-92 - [i12]Sewoong Oh, Pramod Viswanath:
The Composition Theorem for Differential Privacy. CoRR abs/1311.0776 (2013) - [i11]Prateek Jain, Sewoong Oh:
Learning Mixtures of Discrete Product Distributions using Spectral Decompositions. CoRR abs/1311.2972 (2013) - 2012
- [j3]Adam Marcus, David R. Karger, Samuel Madden, Rob Miller, Sewoong Oh:
Counting with the Crowd. Proc. VLDB Endow. 6(2): 109-120 (2012) - [c11]Sahand Negahban, Sewoong Oh, Devavrat Shah:
Iterative ranking from pair-wise comparisons. NIPS 2012: 2483-2491 - [i10]Sahand Negahban, Sewoong Oh, Devavrat Shah:
Iterative Ranking from Pair-wise Comparisons. CoRR abs/1209.1688 (2012) - 2011
- [c10]David R. Karger, Sewoong Oh, Devavrat Shah:
Budget-optimal crowdsourcing using low-rank matrix approximations. Allerton 2011: 284-291 - [c9]David R. Karger, Sewoong Oh, Devavrat Shah:
Iterative Learning for Reliable Crowdsourcing Systems. NIPS 2011: 1953-1961 - [c8]Satish Babu Korada, Andrea Montanari, Sewoong Oh:
Gossip PCA. SIGMETRICS 2011: 209-220 - [i9]Satish Babu Korada, Andrea Montanari, Sewoong Oh:
Gossip PCA. CoRR abs/1103.4195 (2011) - [i8]Amin Karbasi, Sewoong Oh:
Robust Localization from Incomplete Local Information. CoRR abs/1110.3018 (2011) - [i7]David R. Karger, Sewoong Oh, Devavrat Shah:
Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems. CoRR abs/1110.3564 (2011) - 2010
- [j2]Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh:
Matrix Completion from Noisy Entries. J. Mach. Learn. Res. 11: 2057-2078 (2010) - [j1]Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh:
Matrix completion from a few entries. IEEE Trans. Inf. Theory 56(6): 2980-2998 (2010) - [c7]Amin Karbasi, Sewoong Oh:
Distributed sensor network localization from local connectivity: performance analysis for the HOP-TERRAIN algorithm. SIGMETRICS 2010: 61-70 - [i6]Reza Parhizkar, Amin Karbasi, Sewoong Oh, Martin Vetterli:
Calibration for Ultrasound Breast Tomography Using Matrix Completion. CoRR abs/1012.4928 (2010)
2000 – 2009
- 2009
- [c6]Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh:
Low-rank matrix completion with noisy observations: A quantitative comparison. Allerton 2009: 1216-1222 - [c5]Raghunandan H. Keshavan, Sewoong Oh, Andrea Montanari:
Matrix completion from a few entries. ISIT 2009: 324-328 - [c4]Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh:
Matrix Completion from Noisy Entries. NIPS 2009: 952-960 - [i5]Raghunandan H. Keshavan, Sewoong Oh, Andrea Montanari:
Matrix Completion from a Few Entries. CoRR abs/0901.3150 (2009) - [i4]Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh:
Matrix Completion from Noisy Entries. CoRR abs/0906.2027 (2009) - [i3]Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh:
Low-rank Matrix Completion with Noisy Observations: a Quantitative Comparison. CoRR abs/0910.0921 (2009) - [i2]Raghunandan H. Keshavan, Sewoong Oh:
A Gradient Descent Algorithm on the Grassman Manifold for Matrix Completion. CoRR abs/0910.5260 (2009) - 2008
- [c3]Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh:
Learning low rank matrices from O(n) entries. Allerton 2008: 1365-1372 - [c2]Jeremie Ezri, Andrea Montanari, Sewoong Oh, Rüdiger L. Urbanke:
The slope scaling parameter for general channels, decoders, and ensembles. ISIT 2008: 1443-1447 - [c1]Jeremie Ezri, Rüdiger L. Urbanke, Andrea Montanari, Sewoong Oh:
Computing the threshold shift for general channels. ISIT 2008: 1448-1452 - [i1]Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh:
Learning Low Rank Matrices from O(n) Entries. CoRR abs/0812.2599 (2008)
Coauthor Index
[c99] [i110] [i97] [j29] [c92] [i95] [c80] [i74] [c70] [c69] [i68] [i60] [j26] [j25] [j24] [c64] [c63] [c56] [i54] [c54] [c53] [c52] [c50] [c49] [c47] [c45] [i52] [i50] [i44] [i43] [i42] [j18] [j17] [c44] [c42] [i40] [i39] [i38] [i37] [i34] [j15] [j13] [j12] [c40] [c39] [c37] [c36] [i32] [i28] [j11] [j8] [c33] [c31] [c29] [c27] [c25] [i25] [i21] [i19] [j7] [c24] [c22] [c21] [i16] [c15] [i15] [i14] [i13] [i12]
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